Practical applications intelligent systems (117 résultats)

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Taschenbuch. Etat : Neu. Neuware.

Taschenbuch. Etat : Neu. Neuware - CrewAI User GuideArtificial intelligence is evolving beyond single chatbots. Today's most powerful AI solutions are built with teams of intelligent agents that collaborate, delegate tasks, solve complex problems, and automate entire workflows. But learning how to design, manage, and scale these multi-agent systems can feel overwhelming-especially if you're new to CrewAI or AI automation.If you've struggled to understand how AI agents work together, found technical documentation difficult to follow, or wondered how to build reliable AI workflows for real-world projects, this book provides the practical knowledge you need to get started with confidence.CrewAI User Guide is a comprehensive, step-by-step manual that takes you from the fundamentals of CrewAI to building sophisticated, production-ready multi-agent systems. Whether you're a developer, AI enthusiast, business professional, automation specialist, or student, you'll learn how to create intelligent AI teams that can research, analyze, write, reason, collaborate, and automate complex tasks with remarkable efficiency.Inside this book, you'll learn how to: - Install and configure CrewAI correctly from the beginning.- Understand the architecture behind agents, tasks, crews, and workflows.- Design intelligent AI agents with specialized roles and responsibilities.- Build collaborative multi-agent systems for real-world applications.- Integrate Large Language Models (LLMs), APIs, databases, and external tools.- Create dynamic workflows that adapt to changing conditions.- Manage memory, knowledge, and context for more accurate AI responses.- Improve performance, reduce costs, and optimize workflow efficiency.- Protect sensitive information with security, privacy, and responsible AI practices.- Troubleshoot common issues and apply expert techniques to build scalable, enterprise-ready AI applications.Rather than focusing only on theory, this guide emphasizes practical implementation. Every chapter is designed to help you build skills you can immediately apply to personal projects, professional development, and business automation initiatives. As you progress, you'll gain the confidence to move from simple AI experiments to sophisticated workflows capable of handling complex, collaborative tasks.Whether your goal is to automate repetitive work, accelerate software development, improve business processes, enhance research capabilities, or explore the future of intelligent automation, this book provides a clear roadmap for turning ideas into working AI solutions.The future belongs to those who know how to harness collaborative artificial intelligence. Get your copy of CrewAI User Guide today and start building powerful, intelligent AI agent systems that transform the way you work, create, and innovate.…

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Taschenbuch. Etat : Neu. Neuware - AI Agent Projects with Python: Build Practical AI Assistants, Research Agents, Automation Tools, Multi-Agent Systems and Intelligent ApplicationsYou have learned some Python. You have tried AI APIs. Maybe you have even built a chatbot. But when it is time to build an AI agent that can actually use tools, remember information, research a topic, or complete a task, everything suddenly feels more complicated.Which tools should you use How do you connect an AI model to Python functions How does an agent know what action to take next How do you add memory, RAG, automation, or multiple agents without getting lost in confusing documentation and scattered tutorials AI Agent Projects with Python gives you a practical way forward. Instead of filling pages with theory, this book teaches AI agent development by helping you build working projects step by step. You start with the basic structure of an agent and gradually move toward more capable intelligent applications.Inside, you will learn how to build a Python AI assistant, connect language models to tools, manage conversation history, create structured responses, and handle common errors. You will work with Retrieval-Augmented Generation (RAG) to connect agents to external knowledge and add memory so they can preserve useful information across interactions.As your skills grow, you will build research agents, automation agents, data analysis agents, and multi-agent systems. You will see how specialized agents can share work, manage information, and cooperate on larger tasks. You will also bring tools, retrieval, memory, application state, and user interaction together in a more complete intelligent application.The practical examples show you what the code is doing and why it works. You will also learn important development habits that can save you from costly mistakes, including input validation, permissions, execution limits, error handling, human approval, and safe API key management. The book does not stop when your agent starts working. You will learn how to test, evaluate, secure, monitor, and prepare AI agent applications for production. Topics such as logging, tracing, failures, retries, rate limits, cost management, and reliability help you understand what it takes to move beyond a small experiment.You do not need to be an AI researcher. Basic Python knowledge is enough to get started, and important concepts are explained as they appear. The goal is not to make you copy large blocks of code without understanding them. It is to help you develop practical skills you can reuse in your own AI projects. AI agents are quickly becoming an important part of modern software development. Do not spend months jumping between tutorials and trying to piece everything together on your own.Get your copy of AI Agent Projects with Python today and start building practical AI agents one project at a time.…

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Taschenbuch. Etat : Neu. Neuware - Most AI books teach prompts.This book teaches systemsAI agents are no longer simple chatbots. Modern AI systems can reason, plan, use tools, collaborate with other agents, and execute complex workflows with minimal human intervention. Building these systems requires a new engineering discipline-one that combines software architecture, orchestration, memory design, reliability engineering, and autonomous decision-making.What Readers Learn- In this book you'll learn: - What makes a system truly agentic- Agent architecture design patterns- Memory systems and retrieval architectures- Tool-using AI agents- Multi-agent orchestration strategies- Reliability, observability, and safety engineering- Production deployment patterns- Real-world automation blueprints- Research, content, business, productivity, and sales agent systemsWho This Book Is For- This book is ideal for: - Software Engineers- AI Engineers- Architects- Technical Founders- Product Leaders- AI ConsultantsWhether you're building your first autonomous workflow or designing enterprise-scale multi-agent systems, this book provides the practical frameworks, implementation patterns, and production lessons needed to build reliable AI agent systems that work beyond the demo.…

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